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Salesforce Plat-Arch-201 Exam Syllabus Topics:

SectionWeightObjectives
Data Integration20%- Integration patterns and technologies
  • 1. APIs, middleware and external systems integration
  • 2. Synchronous vs asynchronous, batch vs real-time
- External data sources
  • 1. External Objects, OData and virtual data access
- Data synchronization and consistency
  • 1. Conflict resolution, data consistency and idempotency
Data Governance, Quality and Security15%- Data quality management
  • 1. Profiling, monitoring, cleansing and enrichment
- Data security and compliance
  • 1. Access control, encryption, compliance and audit
- Data governance framework
  • 1. Policies, standards, ownership and stewardship
Large Data Volumes and Performance20%- Query and performance optimization
  • 1. Indexing, selective queries and avoiding performance bottlenecks
- Storage and scalability planning
  • 1. Data volume growth planning and storage limits
- LDV architecture design
  • 1. Data distribution, archiving and partitioning strategies
Data Migration15%- Data quality and validation
  • 1. Cleaning, deduplication and post-migration verification
- Migration strategy and planning
  • 1. Assessment, mapping, validation and rollback planning
- Migration execution and tools
  • 1. Data loader, ETL tools and bulk API usage
Data Modeling and Database Design25%- Data skew prevention
  • 1. Avoid record locking, sharing issues and excessive parent-child relationships
- Metadata management
  • 1. Business dictionary, data lineage, taxonomy and classification
- Object type selection
  • 1. Standard/custom objects vs Big Objects: use cases, pros and cons
- Data model design for Customer 360
  • 1. Scalable design aligned with security and sharing model
  • 2. Objects, fields, relationships and object features
Master Data Management5%- MDM implementation approaches
  • 1. Harmonization, consolidation, survivorship rules and thresholds
  • 2. Canonical modeling and hierarchy management
- Golden record and system of truth
  • 1. Establishing single source of truth in single org

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Salesforce Certified Platform Data Architect Sample Questions (Q140-Q145):

NEW QUESTION # 140
Which relationship enforces cascade delete?

Answer: C

Explanation:
In master-detail, deleting the parent deletes all child records.


NEW QUESTION # 141
Universal Containers (UC) is using Salesforce Sales & Service Cloud for B2C sales and customer service but they are experiencing a lot of duplicate customers in the system. Which are two recommended approaches for UC to avoid duplicate data and increase the level of data quality?

Answer: A,B

Explanation:
Using Duplicate Management and Data.com Clean are two recommended approaches for UC to avoid duplicate data and increase the level of data quality. Duplicate Management can prevent or alert users when they try to create or edit records that are duplicates of existing records.
Data.com Clean can compare Salesforce records with Data.com records and provide suggestions for updates or removals of duplicate records.


NEW QUESTION # 142
Northern Trail Outfitters is concerned because some of its data is sensitive and needs to be identified for access. What should be used to provide ways to filter and identify the sensitive data?

Answer: D

Explanation:
According to the official Salesforce guide, data classification metadata is a feature that allows administrators to classify data fields based on their sensitivity level, such as confidential, restricted, or general. Data classification metadata can be used to filter and identify sensitive data fields and apply appropriate security measures, such as encryption, masking, or auditing. Option D is the correct answer because it suggests using data classification metadata to provide ways to filter and identify sensitive data.


NEW QUESTION # 143
UC is having issues using Informatica Cloud Louder to export +10MOrder records. Each Order record has 10 Order Line Items. What two steps can you take to help correct this? Choose two answers.

Answer: B,D

Explanation:
Exporting in multiple batches and using PK Chunking are two steps that can help correct the issues with exporting large volumes of Order records using Informatica Cloud Loader. Exporting in multiple batches can reduce the load on the system and avoid timeouts or errors. Using PK Chunking can split a large data set into smaller chunks based on the record IDs and enable parallel processing of each chunk.


NEW QUESTION # 144
Universal Containers (UC) has several custom Visualforce applications have been developed in which users are able to edit Opportunity records. UC struggles with data completeness on their Opportunity records and has decided to make certain fields required that have not been in the past. The newly required fields are dependent on the Stage of the Opportunity, such that certain fields are only required once an Opportunity advances to later stages. There are two fields. What is the simplest approach to handle this new requirement?

Answer: B

Explanation:
Using a validation rule for each field that takes the Stage into consideration is the simplest approach to handle this new requirement. A validation rule can enforce the field requirements based on the logic and criteria that you define, and display an error message when users try to save a record that does not meet the requirements. Updating the Opportunity page layout to mark these fields as required will not work because page layouts do not support conditional field requirements. Updating these Opportunity field definitions in Setup to be required will not work because it will apply to all stages and records. Writing an Apex trigger that checks each field when records are saved is not the simplest approach because it requires coding and testing


NEW QUESTION # 145
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